•An Analysis Services database is the top level container for other dependent objects:

•A database includes

–Data Source

–Data Source View

–Cube

–Dimension

–Security Role

Basic Into

The basic idea of OLAP is fairly simple. Let’s think about that book ordering data for a moment.

Suppose you want to know how many people ordered a particular book during each month of the year. You could write a fairly simple query to get the information you want.

The catch is that it might take a long time for SQL Server to churn through that many rows of data.

And what if the data was not all in a single SQL Server table, but scattered around in various databases throughout your organization? The customer info, for example, might be in an Oracle database, and supplier information in a legacy xBase database.

The basic idea is to trade off increased storage space now for speed of querying later.

OLAP does this by precalculating and storing aggregates.

When you identify the data that you want to store in an OLAP database, Analysis Services analyzes it in advance and figures out those daily, weekly, and monthly numbers and stores them away (and stores many other aggregations at the same time). This takes up plenty of disk space, but it means that when you want to explore the data you can do so quickly.

Later in the chapter, you’ll see how you can use Analysis Services to extract summary information from your data. First, though, you need to familiarize yourself with a new vocabulary.

The basic concepts of OLAP include:

Cube

Dimension table

Dimension

Hierarchy

Level

Fact table

Measure

Schema

We are going to provide you Detailed level of description in upcoming post covering all aspect of SSAS